DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Status
Claims 1-20 are pending:
Claims 1-8 have been withdrawn.
Claims 9-20 are rejected.
Election/Restrictions
Claims 1-8 have been withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected group I, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 05/11/2026.
Applicant’s election without traverse of group II in the reply filed on 05/11/2026 is acknowledged.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 9-20 are rejected under 35 U.S.C. 103 as being unpatentable over Konishi (WO 2023/013311) in view of Nguyen (WO 2015139115).
Regarding claims 9 and 16, Konishi teaches a method of automatically providing supplies (“[t]he present invention addresses the difficulty of voluntarily performing tasks related to a running out of reagents, maintenance, and the like. A task assistance system 100 is communicatively connected to a medical device 200 and a terminal 300, creates a task list including one or a plurality of tasks recommended to be performed concerning the medical device 200, transmits the created task list to the terminal 300, receives from the terminal 300 information indicating an intention to take charge of a task in the task list, and transmits to the terminal 300 information indicating that the intention to take charge of the task in the task list has been expressed”, see ABS) for home dialysis treatment with a dialysis machine (the medical equipment 200 includes dialysis machine, see pg. 2), and a non-transitory computer-readable media (auxiliary storage device 234 is a silicon disk including a non-volatile semiconductor memory, see pg. 3) storing program instructions that, when executed by the one or more processors (processor 231), cause the one or more processors to perform operations comprising:
receiving, from the dialysis machine, operating data indicating consumption of a first unit of a consumable in conjunction with the home dialysis treatment (“medical device 200 transmits data 240 regarding the remaining amount of consumables and data 250 regarding an alarm generated in the medical device 200 to the work support system 100 via the network. FIG. 3(a) shows data 240 regarding the remaining amount of consumables”, see pg. 3 and “consumables data receiving unit 110 receives data 240 (see FIG. 3a) regarding the remaining amount of consumables from one or more medical devices 200 that can communicate with the work support system 100”, see pg. 5);
estimating a remaining amount of the consumable based on the operating data (data 240 regarding the remaining amount of consumables, see pg. 3; “consumables data receiving unit 110 receives data 240 (see FIG. 3a) regarding the remaining amount of consumables from one or more medical devices 200 that can communicate with the work support system 100”, see pg. 5; Fig. 17 prediction of remaining amount of consumables);
forecasting future demand for the consumable based on the operating data (“by changing the predicted date, it is possible to confirm the prediction of the remaining amount of consumables on the changed predicted date”, see pg. 14)…
Translated Fig. 17 of Konishi
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Konishi does not teach causing a quantity of new units of the consumable to be delivered to a location of the dialysis machine based on a comparison of the forecasted future demand and the estimated remaining amount to be used for subsequent home dialysis treatments.
In a related field of endeavor, Nguyen teaches a system and method for managing illness outside of a hospital environment (see ABS) comprising the step of causing a quantity of new units of the consumable to be delivered to a location of the dialysis machine based on a comparison of the forecasted future demand and the estimated remaining amount to be used for subsequent home dialysis treatments (generating one or more predicted outcome based on the alert rule, see ¶21; the indicators of medical supplies being ordered or consumed by the patient include logistics information related to the delivery of supplies to a patient's residence, see ¶33; the patient interface 208 may also be configured to interface with dialysis machines 216 and other medical devices (e.g. weight scales 212, blood pressure monitors 214, see ¶172; inventory ordering capabilities, see ¶191; supply reordering, see ¶191; see the algorithm may consider supply usage rate, current inventory levels, next scheduled order, the predicted remaining amount at the time of the next scheduled order and the predicted maximum length of time from order date to delivery date to determine whether a user will run out of an item before the next scheduled delivery, see ¶193; predicted supplies used for the treatment may be automatically deducted from a patient's inventory, after patient confirmation/adjustment. This information may also be used to estimate the wear on multiple-use supplies/equipment and predict when these components will need replacing/maintenance, and notify the appropriate users, see ¶200).
It would have been obvious to one of ordinary skill in the effective filing date of the invention to modify the method and the non-transitory computer-readable media of Konishi by incorporating the step of causing a quantity of new units of the consumable to be delivered to a location of the dialysis machine based on a comparison of the forecasted future demand and the estimated remaining amount to be used for subsequent home dialysis treatments as disclosed by Nguyen because it provides a system with better adherence to treatment and clinical prescriptions, improves patient health outcomes and improves efficiency of administrating treatment for both patients and caregivers, saving time and money for those involved with patient care (Nguyen, see ¶74).
Regarding claim 10, Konishi and Nguyen teach the method of Claim 9, further comprising providing, by the dialysis machine, the home dialysis treatment to a patient using new units of the consumable (Konishi, based on the data 240 on the remaining amount of consumables received by the consumables data receiving unit 110, the list creation unit 113 creates a reagent replacement task, which is one or more reagent replacement or replenishment tasks, see pg. 5).
Regarding claim 11, Konishi and Nguyen teach method of Claim 9, wherein estimating the remaining amount of the consumable based on the operating data comprises:
determining, from the operating data, a number of treatment sessions provided by the dialysis machine (Nguyen, “information capture points at the various steps of a treatment, such as beginning a new treatment, following up after a treatment”, see ¶77, “beginning treatment, during treatment, ending treatment, aborting treatment”, see ¶165 and historical treatment information, see ¶166); and
estimating a historical consumption of the consumable based on the number of treatment sessions (Nguyen, “data held in the backend system 300 from patients including the procedure rate…used to predict the usage/consumption of supplies during the treatment”, see ¶200, analytics based upon the historical usage, wastage and consumption patterns related to inventory, see ¶121 and the patient profile also tracks the patient's historical, current, and predicted supply usage information, see ¶207).
Regarding claims 12 and 20. (Original) The method of Claim 9 and non-transitory computer-readable media of Claim 16,
wherein forecasting future demand for the consumable based on the operating data is based on a setting for the dialysis machine (Nguyen, “patient settings may include…which dialysis modality the patient is currently using, and what steps or stages the patient is expected to go through during a treatment”, see ¶158),
the setting associated with a treatment plan for the home dialysis treatment (Nguyen, depending on the settings set by the HCT, future treatments may be scheduled, and inventory items ordered, see ¶170 and the decision support module 302 is also configured to provide suggestions/decision support to the user based on their inputs and settings, see ¶182).
Regarding claims 13 and 17, Konishi and Nguyen teach method of Claim 9 and non-transitory computer-readable media of Claim 16, further comprising providing a user interface comprising an indication of the remaining amount of the consumable or the quantity of new units of the consumable (Konishi, the user of the terminal 300 can indicate his/her intention to be in charge of the work in the work list, see pg. 6 and the communication I/F 302 is an interface for communicably connecting the terminal 300 to the work support system 100 via a network. The input/output I/F 305 receives operation instructions and the like from the user of the terminal 300 who operates the input device connected to the input/output I/F 305, see pg. 8) (Nguyen, supply levels in ¶191 and items may be presented to the user, see ¶191).
Regarding claims 14 and 18, Konishi and Nguyen teach method of Claim 12 and non-transitory computer-readable media of Claim 17, further comprising allowing/enabling a user to adjust the quantity of new units of the consumable via the user interface (Nguyen, an interface for confirming supply count, see ¶52 and an interface for preparing an order for shipment to the patient, see ¶53, inventory ordering capabilities, see ¶191 and in addition to selecting items to order, see ¶193).
Regarding claims 15 and 19, Konishi and Nguyen teach method of Claim 9 and non-transitory computer-readable media of Claim 16, wherein estimating the remaining amount of the consumable is further based on an order history for the consumable (Nguyen, inventory ordering capabilities, see ¶191 and “the predicted maximum length of time from order date to delivery date to determine whether a user will run out of an item before the next scheduled delivery”, see ¶193).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to EKANDRA S. MILLER-CRUZ whose telephone number is (571)270-7849. The examiner can normally be reached M-Th 7 am - 6 pm EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Benjamin L. Lebron can be reached at (571) 272-0475. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/EKANDRA S. MILLER-CRUZ/ Primary Examiner, Art Unit 1773
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